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stdlib-bot committed Jan 18, 2025
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1 change: 0 additions & 1 deletion CHANGELOG.md
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Expand Up @@ -7281,7 +7281,6 @@ A total of 23 people contributed to this release. Thank you to the following con

<details>

- [`fb901fb`](https://github.com/stdlib-js/stdlib/commit/fb901fb3b51f47c79c0fae95afe75be9cb198b2a) - **docs:** update namespace table of contents [(#4796)](https://github.com/stdlib-js/stdlib/pull/4796) _(by stdlib-bot)_
- [`22a3dcf`](https://github.com/stdlib-js/stdlib/commit/22a3dcfe916b7f5c979d6ee93045d37add5d685d) - **docs:** update namespace TypeScript declaration comments [(#4794)](https://github.com/stdlib-js/stdlib/pull/4794) _(by stdlib-bot, Philipp Burckhardt)_
- [`ce23df1`](https://github.com/stdlib-js/stdlib/commit/ce23df1c97ca2955cfeaea2c539f63d64d655612) - **feat:** add C implementation for `stats/base/dists/degenerate/pdf` [(#4585)](https://github.com/stdlib-js/stdlib/pull/4585) _(by Karan Anand, stdlib-bot)_
- [`0f54105`](https://github.com/stdlib-js/stdlib/commit/0f54105c71aac4e8f188bda700ef98dc094c78d9) - **feat:** add C implementation for `stats/base/dists/degenerate/pmf` [(#4586)](https://github.com/stdlib-js/stdlib/pull/4586) _(by Karan Anand, stdlib-bot)_
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25 changes: 9 additions & 16 deletions README.md
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Expand Up @@ -103,13 +103,13 @@ The namespace contains the following statistical functions:
- <span class="signature">[`dmaxabssorted( N, x, strideX )`][@stdlib/stats/base/dmaxabssorted]</span><span class="delimiter">: </span><span class="description">calculate the maximum absolute value of a sorted double-precision floating-point strided array.</span>
- <span class="signature">[`dmaxsorted( N, x, strideX )`][@stdlib/stats/base/dmaxsorted]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a sorted double-precision floating-point strided array.</span>
- <span class="signature">[`dmean( N, x, stride )`][@stdlib/stats/base/dmean]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array.</span>
- <span class="signature">[`dmeankbn( N, x, strideX )`][@stdlib/stats/base/dmeankbn]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array using an improved Kahan–Babuška algorithm.</span>
- <span class="signature">[`dmeankbn( N, x, stride )`][@stdlib/stats/base/dmeankbn]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array using an improved Kahan–Babuška algorithm.</span>
- <span class="signature">[`dmeankbn2( N, x, strideX )`][@stdlib/stats/base/dmeankbn2]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array using a second-order iterative Kahan–Babuška algorithm.</span>
- <span class="signature">[`dmeanli( N, x, strideX )`][@stdlib/stats/base/dmeanli]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array using a one-pass trial mean algorithm.</span>
- <span class="signature">[`dmeanli( N, x, stride )`][@stdlib/stats/base/dmeanli]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array using a one-pass trial mean algorithm.</span>
- <span class="signature">[`dmeanlipw( N, x, stride )`][@stdlib/stats/base/dmeanlipw]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array using a one-pass trial mean algorithm with pairwise summation.</span>
- <span class="signature">[`dmeanors( N, x, strideX )`][@stdlib/stats/base/dmeanors]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array using ordinary recursive summation.</span>
- <span class="signature">[`dmeanors( N, x, stride )`][@stdlib/stats/base/dmeanors]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array using ordinary recursive summation.</span>
- <span class="signature">[`dmeanpn( N, x, stride )`][@stdlib/stats/base/dmeanpn]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array using a two-pass error correction algorithm.</span>
- <span class="signature">[`dmeanpw( N, x, strideX )`][@stdlib/stats/base/dmeanpw]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array using pairwise summation.</span>
- <span class="signature">[`dmeanpw( N, x, stride )`][@stdlib/stats/base/dmeanpw]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array using pairwise summation.</span>
- <span class="signature">[`dmeanstdev( N, correction, x, strideX, out, strideOut )`][@stdlib/stats/base/dmeanstdev]</span><span class="delimiter">: </span><span class="description">calculate the mean and standard deviation of a double-precision floating-point strided array.</span>
- <span class="signature">[`dmeanstdevpn( N, correction, x, strideX, out, strideOut )`][@stdlib/stats/base/dmeanstdevpn]</span><span class="delimiter">: </span><span class="description">calculate the mean and standard deviation of a double-precision floating-point strided array using a two-pass algorithm.</span>
- <span class="signature">[`dmeanvar( N, correction, x, strideX, out, strideOut )`][@stdlib/stats/base/dmeanvar]</span><span class="delimiter">: </span><span class="description">calculate the mean and variance of a double-precision floating-point strided array.</span>
Expand Down Expand Up @@ -150,11 +150,11 @@ The namespace contains the following statistical functions:
- <span class="signature">[`dnanvarianceyc( N, correction, x, stride )`][@stdlib/stats/base/dnanvarianceyc]</span><span class="delimiter">: </span><span class="description">calculate the variance of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and Cramer.</span>
- <span class="signature">[`drange( N, x, strideX )`][@stdlib/stats/base/drange]</span><span class="delimiter">: </span><span class="description">calculate the range of a double-precision floating-point strided array.</span>
- <span class="signature">[`dsem( N, correction, x, stride )`][@stdlib/stats/base/dsem]</span><span class="delimiter">: </span><span class="description">calculate the standard error of the mean of a double-precision floating-point strided array.</span>
- <span class="signature">[`dsemch( N, correction, x, strideX )`][@stdlib/stats/base/dsemch]</span><span class="delimiter">: </span><span class="description">calculate the standard error of the mean of a double-precision floating-point strided array using a one-pass trial mean algorithm.</span>
- <span class="signature">[`dsemch( N, correction, x, stride )`][@stdlib/stats/base/dsemch]</span><span class="delimiter">: </span><span class="description">calculate the standard error of the mean of a double-precision floating-point strided array using a one-pass trial mean algorithm.</span>
- <span class="signature">[`dsempn( N, correction, x, stride )`][@stdlib/stats/base/dsempn]</span><span class="delimiter">: </span><span class="description">calculate the standard error of the mean of a double-precision floating-point strided array using a two-pass algorithm.</span>
- <span class="signature">[`dsemtk( N, correction, x, strideX )`][@stdlib/stats/base/dsemtk]</span><span class="delimiter">: </span><span class="description">calculate the standard error of the mean of a double-precision floating-point strided array using a one-pass textbook algorithm.</span>
- <span class="signature">[`dsemtk( N, correction, x, stride )`][@stdlib/stats/base/dsemtk]</span><span class="delimiter">: </span><span class="description">calculate the standard error of the mean of a double-precision floating-point strided array using a one-pass textbook algorithm.</span>
- <span class="signature">[`dsemwd( N, correction, x, strideX )`][@stdlib/stats/base/dsemwd]</span><span class="delimiter">: </span><span class="description">calculate the standard error of the mean of a double-precision floating-point strided array using Welford's algorithm.</span>
- <span class="signature">[`dsemyc( N, correction, x, strideX )`][@stdlib/stats/base/dsemyc]</span><span class="delimiter">: </span><span class="description">calculate the standard error of the mean of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer.</span>
- <span class="signature">[`dsemyc( N, correction, x, stride )`][@stdlib/stats/base/dsemyc]</span><span class="delimiter">: </span><span class="description">calculate the standard error of the mean of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer.</span>
- <span class="signature">[`dsmean( N, x, stride )`][@stdlib/stats/base/dsmean]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using extended accumulation and returning an extended precision result.</span>
- <span class="signature">[`dsmeanors( N, x, stride )`][@stdlib/stats/base/dsmeanors]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation and returning an extended precision result.</span>
- <span class="signature">[`dsmeanpn( N, x, stride )`][@stdlib/stats/base/dsmeanpn]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm with extended accumulation and returning an extended precision result.</span>
Expand Down Expand Up @@ -234,7 +234,7 @@ The namespace contains the following statistical functions:
- <span class="signature">[`scumin( N, x, strideX, y, strideY )`][@stdlib/stats/base/scumin]</span><span class="delimiter">: </span><span class="description">calculate the cumulative minimum of single-precision floating-point strided array elements.</span>
- <span class="signature">[`scuminabs( N, x, strideX, y, strideY )`][@stdlib/stats/base/scuminabs]</span><span class="delimiter">: </span><span class="description">calculate the cumulative minimum absolute value of single-precision floating-point strided array elements.</span>
- <span class="signature">[`sdsmean( N, x, stride )`][@stdlib/stats/base/sdsmean]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using extended accumulation.</span>
- <span class="signature">[`sdsmeanors( N, x, strideX )`][@stdlib/stats/base/sdsmeanors]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation.</span>
- <span class="signature">[`sdsmeanors( N, x, stride )`][@stdlib/stats/base/sdsmeanors]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation.</span>
- <span class="signature">[`sdsnanmean( N, x, stride )`][@stdlib/stats/base/sdsnanmean]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using extended accumulation.</span>
- <span class="signature">[`sdsnanmeanors( N, x, stride )`][@stdlib/stats/base/sdsnanmeanors]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using ordinary recursive summation with extended accumulation.</span>
- <span class="signature">[`smax( N, x, strideX )`][@stdlib/stats/base/smax]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a single-precision floating-point strided array.</span>
Expand Down Expand Up @@ -300,7 +300,7 @@ The namespace contains the following statistical functions:
- <span class="signature">[`svariancepn( N, correction, x, stride )`][@stdlib/stats/base/svariancepn]</span><span class="delimiter">: </span><span class="description">calculate the variance of a single-precision floating-point strided array using a two-pass algorithm.</span>
- <span class="signature">[`svariancetk( N, correction, x, strideX )`][@stdlib/stats/base/svariancetk]</span><span class="delimiter">: </span><span class="description">calculate the variance of a single-precision floating-point strided array using a one-pass textbook algorithm.</span>
- <span class="signature">[`svariancewd( N, correction, x, stride )`][@stdlib/stats/base/svariancewd]</span><span class="delimiter">: </span><span class="description">calculate the variance of a single-precision floating-point strided array using Welford's algorithm.</span>
- <span class="signature">[`svarianceyc( N, correction, x, strideX )`][@stdlib/stats/base/svarianceyc]</span><span class="delimiter">: </span><span class="description">calculate the variance of a single-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer.</span>
- <span class="signature">[`svarianceyc( N, correction, x, stride )`][@stdlib/stats/base/svarianceyc]</span><span class="delimiter">: </span><span class="description">calculate the variance of a single-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer.</span>
- <span class="signature">[`variance( N, correction, x, stride )`][@stdlib/stats/base/variance]</span><span class="delimiter">: </span><span class="description">calculate the variance of a strided array.</span>
- <span class="signature">[`variancech( N, correction, x, stride )`][@stdlib/stats/base/variancech]</span><span class="delimiter">: </span><span class="description">calculate the variance of a strided array using a one-pass trial mean algorithm.</span>
- <span class="signature">[`variancepn( N, correction, x, stride )`][@stdlib/stats/base/variancepn]</span><span class="delimiter">: </span><span class="description">calculate the variance of a strided array using a two-pass algorithm.</span>
Expand Down Expand Up @@ -370,11 +370,6 @@ For more information on the project, filing bug reports and feature requests, an

---

## License

See [LICENSE][stdlib-license].


## Copyright

Copyright &copy; 2016-2025. The Stdlib [Authors][stdlib-authors].
Expand Down Expand Up @@ -421,8 +416,6 @@ Copyright &copy; 2016-2025. The Stdlib [Authors][stdlib-authors].
[esm-readme]: https://github.com/stdlib-js/stats-base/blob/esm/README.md
[branches-url]: https://github.com/stdlib-js/stats-base/blob/main/branches.md

[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/stats-base/main/LICENSE

<!-- <toc-links> -->

[@stdlib/stats/base/cumax]: https://github.com/stdlib-js/stats-base-cumax
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